Custom Deep Learning Network for Xilinx FPGA target
4 次查看(过去 30 天)
显示 更早的评论
I am researching on building deep learning accelerators on Xilinx FPGA using the Deep Learning HDL Toolbox. I have a custom CNN network that has an input layer size of [1 1024 2]. Using the ProcessorConfig Class, I'm trying to optimize the processor configuration for my custom CNN network with the optimizeConfigurationForNetwork helper.
The optimize processor is generated sucessfully, but while trying to estimate performance of the CNN network i get the following error:
The Conv module in the processor configuration has an InputMemorySize of [150 150 7]. This is insufficient to delploy the 'AP1' Layer. Increase the InputMemorySize to [171 171 7] or more using hPC.setModuleProperty('conv', 'InputMemorySize', [171 171 7]), where hPC is the dlhdl.ProcessorConfig object.
I've tried to increase the InputMemorySize, but the error keeps being thrown with a higher inputMemorySize requirement for the 2D Average Pooling layer.
I'd appreciate you recommendation on how i could fix this. Thank you.
Paul Osinowo,
Graduate Student
University of Strathclyde, Glasgow.
3 个评论
Umar
2024-7-8
Hi Paul,
Thank you for your feedback. I'm glad to hear that you found the information helpful. It's great that you were able to identify the issue with the output of the layer on top of the 2D Average Pooling Layer and make the necessary modifications to fix the error. If you have any further questions or need assistance with anything else, please don't hesitate to reach out.
回答(0 个)
另请参阅
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!